





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A							   =							logging.get_logger(__name__)

__A							   =							{
    "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json",
    "google/bigbird-roberta-large": "https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json",
    "google/bigbird-base-trivia-itc": "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''
 lowercase_						=     "big_bird"

 def __init__(self							:  List[str]			,					UpperCAmelCase_							:  int=50_358			,					UpperCAmelCase_							:  List[str]=768			,					UpperCAmelCase_							:  Optional[int]=12			,					UpperCAmelCase_							:  Union[str, Any]=12			,					UpperCAmelCase_							:  Optional[Any]=3_072			,					UpperCAmelCase_							:  Union[str, Any]="gelu_new"			,					UpperCAmelCase_							:  Any=0.1			,					UpperCAmelCase_							:  List[Any]=0.1			,					UpperCAmelCase_							:  Optional[Any]=4_096			,					UpperCAmelCase_							:  Union[str, Any]=2			,					UpperCAmelCase_							:  Optional[Any]=0.02			,					UpperCAmelCase_							:  Tuple=1E-1_2			,					UpperCAmelCase_							:  Optional[Any]=True			,					UpperCAmelCase_							:  Dict=0			,					UpperCAmelCase_							:  List[str]=1			,					UpperCAmelCase_							:  Dict=2			,					UpperCAmelCase_							:  Optional[Any]=66			,					UpperCAmelCase_							:  Optional[Any]="block_sparse"			,					UpperCAmelCase_							:  Any=True			,					UpperCAmelCase_							:  List[str]=False			,					UpperCAmelCase_							:  Optional[Any]=64			,					UpperCAmelCase_							:  List[Any]=3			,					UpperCAmelCase_							:  int=None			,					**UpperCAmelCase_							:  Optional[Any]			,					)			->Dict:



   '''simple docstring'''



   super().__init__(
       pad_token_id=UpperCAmelCase_			,					bos_token_id=UpperCAmelCase_			,					eos_token_id=UpperCAmelCase_			,					sep_token_id=UpperCAmelCase_			,					**UpperCAmelCase_			,					)

   lowerCamelCase__: List[Any]         =vocab_size
   lowerCamelCase__: str         =max_position_embeddings
   lowerCamelCase__: Union[str, Any]         =hidden_size
   lowerCamelCase__: Optional[Any]         =num_hidden_layers
   lowerCamelCase__: Union[str, Any]         =num_attention_heads
   lowerCamelCase__: Optional[Any]         =intermediate_size
   lowerCamelCase__: Dict         =hidden_act
   lowerCamelCase__: List[str]         =hidden_dropout_prob
   lowerCamelCase__: Optional[int]         =attention_probs_dropout_prob
   lowerCamelCase__: List[Any]         =initializer_range
   lowerCamelCase__: Union[str, Any]         =type_vocab_size
   lowerCamelCase__: Any         =layer_norm_eps
   lowerCamelCase__: Tuple         =use_cache

   lowerCamelCase__: Optional[int]         =rescale_embeddings
   lowerCamelCase__: int         =attention_type
   lowerCamelCase__: List[str]         =use_bias
   lowerCamelCase__: int         =block_size
   lowerCamelCase__: Tuple         =num_random_blocks
   lowerCamelCase__: Union[str, Any]         =classifier_dropout



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''

 @property
 def 				SCREAMING_SNAKE_CASE_   (self							:  Union[str, Any])			->Mapping[str, Mapping[int, str]]:



   '''simple docstring'''



   if self.task == "multiple-choice":
     lowerCamelCase__: Optional[int]         ={0: "batch", 1: "choice", 2: "sequence"}
   else:
     lowerCamelCase__: str         ={0: "batch", 1: "sequence"}
   return OrderedDict(
       [
           ("input_ids", dynamic_axis),
           ("attention_mask", dynamic_axis),
       ])









'''simple docstring'''





from __future__ import annotations

import os
from collections.abc import Mapping

_UpperCamelCase						:						Any  =					tuple[int, int]


class  snake_case__      :




					def __init__(  self  :		List[str]				, _A  :		set[int]				, _A  :		Mapping[EdgeT, int]      )    ->							None:
								UpperCAmelCase_      :       set[int]          =       vertices
								UpperCAmelCase_      :       dict[EdgeT, int]          =       {
								    (min(_A      ), max(_A      )): weight for edge, weight in edges.items()
								}




					def 		A      (  self  :		Union[str, Any]				, _A  :		EdgeT				, _A  :		int      )    ->							None:
								self.vertices.add(edge[0]      )
								self.vertices.add(edge[1]      )
								UpperCAmelCase_      :       List[str]          =       weight





					def 		A      (  self  :		str      )    ->							Graph:
								UpperCAmelCase_      :       Graph          =       Graph({min(self.vertices      )}				, {}      )
								UpperCAmelCase_      :       EdgeT
								UpperCAmelCase_      :       int
								UpperCAmelCase_      :       EdgeT
								UpperCAmelCase_      :       int

								while len(subgraph.vertices      ) < len(self.vertices      ):
											UpperCAmelCase_      :       Optional[Any]          =       max(self.edges.values()      ) + 1
											for edge, weight in self.edges.items():
														if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
																	if weight < min_weight:
																				UpperCAmelCase_      :       Dict          =       edge
																				UpperCAmelCase_      :       Tuple          =       weight

											subgraph.add_edge(_A				, _A      )

								return subgraph






def __UpperCAmelCase   (					A					:			str = "p107_network.txt"		)    ->   int:
			UpperCAmelCase_      :       str          =       os.path.abspath(os.path.dirname(A		)		)
			UpperCAmelCase_      :       str          =       os.path.join(A			,       A		)
			UpperCAmelCase_      :       dict[EdgeT, int]          =       {}
			UpperCAmelCase_      :       list[str]
			UpperCAmelCase_      :       int
			UpperCAmelCase_      :       int

			with open(A		) as f:
						UpperCAmelCase_      :       int          =       f.read().strip().split('''\n'''		)

			UpperCAmelCase_      :       Any          =       [line.split(''','''		) for line in data]

			for edgea in range(1			,       len(A		)		):
						for edgea in range(A		):
									if adjaceny_matrix[edgea][edgea] != "-":
												UpperCAmelCase_      :       Optional[int]          =       int(adjaceny_matrix[edgea][edgea]		)

			UpperCAmelCase_      :       Graph          =       Graph(set(range(len(A		)		)		)			,       A		)

			UpperCAmelCase_      :       Graph          =       graph.prims_algorithm()

			UpperCAmelCase_      :       int          =       sum(graph.edges.values()		)
			UpperCAmelCase_      :       int          =       sum(subgraph.edges.values()		)

			return initial_total - optimal_total


if __name__ == "__main__":
						print(f'''{solution() = }''')


